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viridis-agent-fleet

viridis-agent-fleet

by jdhart81
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

trust__score_agent

Retrieve a decay-weighted trust score and tier for any agent, with a neutral prior for unknown agents.

Instructions

[trust — decay-weighted reputation + trust attestations] Get an agent's decay-weighted trust score in [0,1] and tier. Unknown agents get a neutral 0.5 prior — no blind trust, no unfair zero.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "agent_id": "<agent_id>"
    },
    "name": "trust__score_agent"
  }
}

Input Schema

NameRequiredDescriptionDefault
agent_idYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changedv0.1.11
    • addedInput schema / properties / agent_id / title
      Added value: +"Agent Id"
    • addedInput schema / title
      Added value: +"score_agentArguments"
  2. Changed2 schema fields changedv0.1.9
    • removedInput schema / properties / agent_id / title
      Removed value: -"Agent Id"
    • removedInput schema / title
      Removed value: -"score_agentArguments"
  3. Changed2 schema fields changed
    • addedInput schema / properties / agent_id / title
      Added value: +"Agent Id"
    • addedInput schema / title
      Added value: +"score_agentArguments"
  4. Changed2 schema fields changed
    • removedInput schema / properties / agent_id / title
      Removed value: -"Agent Id"
    • removedInput schema / title
      Removed value: -"score_agentArguments"
  5. First observed

TDQS

A3.8/5.0
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Despite no annotations, the description discloses key behaviors: decay-weighted computation, output range [0,1] and tier, and neutral prior for unknown agents. It does not state whether the tool is read-only or requires permissions, but it adds value beyond the input schema.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two concise sentences with a brief prefix. Every sentence adds value: the first states purpose, the second clarifies edge-case behavior. No unnecessary words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's simplicity (one parameter, no output schema), the description covers the main output and special behavior (neutral prior). However, it lacks details on possible error cases, tier values, and the agent_id parameter, making it slightly incomplete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0% with no description for the single parameter 'agent_id'. The description does not compensate by explaining the parameter format, source, or constraints, leaving ambiguity for the agent.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states 'Get an agent's decay-weighted trust score in [0,1] and tier,' specifying the action (Get), resource (trust score and tier), and scope. It distinguishes from sibling tools like trust__attest, trust__record_outcome, etc., which handle different trust operations.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explains that unknown agents receive a neutral 0.5 prior, clarifying the tool's behavior for new agents. While it does not explicitly list when to avoid this tool, the context of sibling tools and the distinct purpose imply appropriate usage.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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